1. Field of the Invention
The invention pertains to the field of video compression and decompression systems. More particularly, the invention pertains to a system and method for reducing compression artifacts in a video compression and decompression system.
2. Description of the Related Art
Systems for applications of video and visual communications transmit, process and store large quantities of video data. To create a video presentation, such as a video movie, a rendering video system displays the video data as a sequence of individual digital images, also referred to as “frames,” thereby simulating movement. In order to achieve a video presentation with an acceptable video quality, or to enable transmission and storage at all, the video systems process and modify the video data prior to transmission or storage. For instance, the video data is compressed and encoded to reduce the bit rate and the required bandwidth for storage and transmission of the images.
In a conventional video system a video encoder is used to compress and encode the video data and a video decoder is used to decompress and to decode the video data. The video encoder outputs video data that has a reduced bit rate and a reduced redundancy. That is, the technique of video compression removes spatial redundancy within a video frame or temporal redundancy between consecutive video frames. In accordance with known image compression standards, such as MPEG, MPEG-2 and JPEG, an image coding process typically includes performing a block based frequency transform, e.g., discrete cosine transform (DCT), on an image to be transmitted. The resulting DCT coefficients are quantized or mapped to different quantization steps to render an approximate representation thereof. If the available transmission bandwidth is relatively small, with respect to the complexity of the image to be transmitted, the size of the quantization steps needs to be relatively large. In that case, the resulting coarse quantization of the DCT coefficients introduces coding artifacts into the transmitted image and severely degrades the visual quality of the decoded sequence that may be displayed.
Examples of such artifacts include mosquito artifacts and blocking artifacts. Mosquito artifacts are defined as temporarily nonstationary impulses that appear around objects which are moving within a decompressed video sequence. The mosquito artifacts result from the coarse quantization of a prediction error signal. The majority of the energy contained in the prediction error signal is the result of a motion estimator's inability to distinguish between differently moving objects within the video sequence. For example, in videoconferencing applications the subject is generally against a stationary background. Since the motion estimator tries to match blocks of pixels between temporarily adjacent frames, the boundaries between moving objects and stationary background that fall within these blocks cannot be detected. This leads to a situation where either a part of the background is assumed to be moving, or a part of the moving object is assumed to be stationary. If these prediction errors are coarsely quantized, impulsive artifacts result that change over time and tend to swarm around the moving object, similar to a mosquito.
Blocking artifacts are defined as the introduction of artificial block boundaries into the decoded video sequence. These artifacts are due to the combination of quantization and dividing the prediction error signal into blocks. That is, since there exists an inverse relationship between spatial extent and frequency extent analogous to the inverse relationship that exists between time and frequency extent in Fourier analysis, the quantization errors that occur in the DCT domain are smeared across the corresponding spatial block. Furthermore, since each block is quantized separately, the errors are most visible at the block boundaries.
In order to reduce the effects of the coding artifacts, it is known to apply a postprocessing technique to the recovered image. Since the artifacts typically comprise high frequency components, decoders in systems that apply such postprocessing include a postprocessor having a low-pass filter to filter out those components in the recovered image. However, the quality of the postprocessed image is dependent upon the selected parameters and may drastically vary from one set of parameters to another.
Other systems use postprocessing filters that are spatially adaptive. These spatially adapted filters rely on local signal estimates and local noise power estimates to alter their responses. However, such an estimation of the noise power based on the quantization step size is not a reliable indicator as to the spatial location of mosquito artifacts and blocking artifacts within the decompressed video. For example, oversmoothing or blurring of the decompressed video occurs due to inaccurate estimates of the compressed video's signal-to-noise ratio.
Thus, there is a need for a video compression and decompressing system and a method which suppress mosquito and blocking artifacts to improve upon the video quality a viewer perceives.